准则权重信息不完全的证据推理多属性决策算法

Evidence Reasoning Algorithm for Multi-criteria Decision-making with Incomplete Attribute Weight Information

针对准则权重信息不完全情况下的多属性决策问题,提出了一种新的证据推理多属性决策算法,它通过建立基于证据信息熵的决策模型来求解准则的最优权重系数,利用求解得到的权重系数和递归ER算法求出各方案的效用值,进而得到各方案的优劣次序。最后,通过算例分析验证了该方法的有效性和合理性。

To solve the problem of multi-criteria decision making in which the information on the weights of criteria are incomplete,a new evidence reasoning algorithm for multi-criteria decision- making is proposed ,which uses the decision-making model built on the base of evidence information entropy to obtain the optimal weights, and the Evidence Reasoning algorithm （ER algorithm） is used to evaluate the alternatives efficiency, and the alternatives can be ranked by the efficiency score. Finally, the effectiveness and rationality of the proposed algorithm are verified by the illustrative example.